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| Section | Weight | Objectives |
|---|---|---|
| Data Cloud & Grounding | 20% | - Data integration for AI agents
|
| Prompt Engineering | 20% | - Prompt Builder usage
|
| Governance & Observability | 10% | - AI governance
|
| AI Agents | 35% | - Agent setup and orchestration
|
| Testing, Deployment & Lifecycle | 15% | - Agent lifecycle management
|
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NEW QUESTION # 56
Universal Containers (UC) plans to implement prompt templates that utilize the standard foundation models. What should UC consider when building prompt templates in Prompt Builder?
Answer: C
Explanation:
UC is using Prompt Builder with standard foundation models (e.g., via Atlas Reasoning Engine).
NEW QUESTION # 57
An Agentforce is tasked with analyzing Agent interactions looking into user inputs, requests, and queries to identify patterns and trends. What functionality allows the AX Specialist to achieve this?
Answer: B
Explanation:
The User Utterances dashboard (Option A) is the correct functionality for analyzing user inputs, requests, and queries to identify patterns and trends. This dashboard aggregates and categorizes the natural language inputs (utterances) from users, enabling the Agentforce Specialist to:
Identify Common Queries: Surface frequently asked questions or recurring issues.
Detect Intent Patterns: Understand how users phrase requests, which helps refine intent detection models.
Improve Bot Training: Highlight gaps in training data or misclassified utterances that require adjustment.
NEW QUESTION # 58
Universal Containers (UC) is creating a new custom prompt template to populate a field with generated output. UC enabled the Einstein Trust Layer to ensure AI Audit data is captured and monitored for adoption and possible enhancements. Which prompt template type should UC use and which consideration should UC review?
Answer: C
Explanation:
Salesforce Agentforce provides various prompt template types to support AI-driven tasks, such as generating text or populating fields. In this case, UC needs a custom prompt template to populate a field with generated output, which directly aligns with the Field Generation prompt template type. This type is designed to use generative AI to create field values (e.g., summaries, descriptions) based on input data or prompts, making it the ideal choice for UC's requirement.
Additionally, UC has enabled the Einstein Trust Layer, a governance framework that ensures AI outputs are safe, explainable, and auditable, capturing AI Audit data for monitoring adoption and identifying improvement areas.
The consideration UC should review is whether Dynamic Fields is enabled. Dynamic Fields allow the prompt template to incorporate variable data from Salesforce records (e.g., case details, customer info) into the prompt, ensuring the generated output is contextually relevant to each record. This is critical for field population tasks, as static prompts wouldn't adapt to record-specific needs. The Einstein Trust Layer further benefits from this, as it can track how dynamic inputs influence outputs for audit purposes.
NEW QUESTION # 59
Universal Containers (UC) configured a new PDF file ingestion in Data Cloud with all the required fields, and also created the mapping and the search Index. UC Is now setting up the retriever and notices a required fleld is missing. How should UC resolve this?
Answer: A
Explanation:
Why is "Update the search index to include the desired field" the correct answer?
When configuring a retriever in Data Cloud for PDF file ingestion, all necessary fields must be included in the search index. If a required field is missing, the correct action is to update the search index to ensure it is available for retrieval.
Key Considerations for Fixing Missing Fields in Data Cloud Retrievers:
Search Index Controls Which Fields Are Searchable
The search index defines which fields are indexed and accessible to the retriever.
If a field is missing, it must be added to the index before it can be queried.
Ensures Complete and Accurate Data Retrieval
Without indexing, the retriever cannot reference the missing field in AI responses.
Updating the index makes the field available for AI-powered retrieval.
Supports AI-Grounded Responses
Agentforce relies on Retriever-Augmented Generation (RAG) to ground AI responses in searchable Data Cloud content.
Ensuring all relevant fields are indexed improves AI-generated answer accuracy.
NEW QUESTION # 60
Universal Containers wants to leverage the Record Snapshots grounding feature in a prompt template. What preparations are required?
Answer: C
Explanation:
Record Snapshots in Salesforce Prompt Builder leverage the data visible on the user's page layout for an object to ground the prompt. This means that the fields and related lists that are configured on the page layout directly influence the data included in the snapshot.
NEW QUESTION # 61
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